{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:59:47Z","timestamp":1760151587045,"version":"build-2065373602"},"reference-count":48,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,4,11]],"date-time":"2022-04-11T00:00:00Z","timestamp":1649635200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Natural Science Foundation of Hebei Province of China","award":["E2018202282"],"award-info":[{"award-number":["E2018202282"]}]},{"name":"the key project of Tianjin Natural Science Foundation","award":["19JCZDJC32100"],"award-info":[{"award-number":["19JCZDJC32100"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>This study aims to symmetrically improve the economy and environmental protection of combined cooling, heating and power microgrid. Hence, the characteristics of configuration ways of energy storage devices in traditional combined cooling, heating and power systems are analyzed, and a scheme for the operator to establish an energy storage station is designed. An improved aquila optimizer for the optimal configuration of the system is proposed to symmetrically enhance the economic and environmental protection performance. The feasibility of the proposed scheme is verified through experiments in three different places. The results show that the economic cost and exhaust emission of the system with energy storage station are reduced to varying degrees compared with the system with energy storage equipment alone and the system without energy storage equipment based on symmetry concept. Especially in Place 1, the scheme with energy storage station in the system can reduce the electric energy purchased from power grid by 43.29% and 61.09%, respectively, compared with other schemes. This study is conducive to promoting the development of clean energy, alleviating the energy crisis, reducing the power supply pressure of power grid, and improving the profits of operators by symmetrically considering the economic and environmental performance of the system.<\/jats:p>","DOI":"10.3390\/sym14040791","type":"journal-article","created":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T22:48:45Z","timestamp":1649803725000},"page":"791","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Design and Optimization of Combined Cooling, Heating, and Power Microgrid with Energy Storage Station Service"],"prefix":"10.3390","volume":"14","author":[{"given":"Nan","family":"Ning","sequence":"first","affiliation":[{"name":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China"},{"name":"Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300130, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2488-7921","authenticated-orcid":false,"given":"Yu-Wei","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China"},{"name":"Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300130, China"}]},{"given":"Hai-Yue","family":"Yang","sequence":"additional","affiliation":[{"name":"Hengshui Power Supply Branch of State Grid Hebei Power Co., Ltd., Hengshui 053000, China"}]},{"given":"Ling-Ling","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300130, China"},{"name":"Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability of Hebei Province, Hebei University of Technology, Tianjin 300130, China"}]}],"member":"1968","published-online":{"date-parts":[[2022,4,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1913","DOI":"10.1007\/s10098-021-02088-x","article-title":"A hierarchical genetic algorithm and mixed-integer linear programming-based stochastic optimization of the configuration of integrated trigeneration energy systems","volume":"23","author":"Zhang","year":"2021","journal-title":"Clean Technol. Environ. Policy"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"315","DOI":"10.1016\/j.egyr.2020.01.010","article-title":"A new optimized configuration for capacity and operation improvement of CCHP system based on developed owl search algorithm","volume":"6","author":"Cao","year":"2020","journal-title":"Energy Rep."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"115073","DOI":"10.1016\/j.enconman.2021.115073","article-title":"Investigation of a hybrid renewable-based grid-independent electricity-heat nexus: Impacts of recovery and thermally storing waste heat and electricity","volume":"252","author":"Hassan","year":"2022","journal-title":"Energy Convers. Manag."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2997","DOI":"10.1002\/er.5993","article-title":"Comprehensive energy cooperative optimization model based on energy conversion efficiency considering investment benefit","volume":"45","author":"Peng","year":"2021","journal-title":"Int. J. Energy Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"117619","DOI":"10.1016\/j.apenergy.2021.117619","article-title":"Integrated energy systems with CCHP and hydrogen supply: A new outlet for curtailed wind power","volume":"303","author":"Li","year":"2021","journal-title":"Appl. Energy"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1222","DOI":"10.1016\/j.renene.2021.09.016","article-title":"Integrating renewables into stand-alone hybrid systems meeting electric, heating, and cooling loads: A case study","volume":"180","author":"Das","year":"2021","journal-title":"Renew. Energy"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Dong, H., Fang, Z., Ibrahim, A., and Cai, J. (2022). Optimized Operation of Integrated Energy Microgrid with Energy Storage Based on Short-Term Load Forecasting. Electronics, 11.","DOI":"10.3390\/electronics11010022"},{"key":"ref_8","unstructured":"Namnabat, M., and Nazari, M.E. (2019, January 29). The effects of PV\/T utilization on short-term scheduling of integrated distributed CHP system. Proceedings of the 24th Electrical Power Distribution Conference, Khoramabad, Iran."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"113911","DOI":"10.1016\/j.enconman.2021.113911","article-title":"Stochastic multi-scenario optimization for a hybrid combined cooling, heating and power system considering multi-criteria","volume":"233","author":"Yan","year":"2021","journal-title":"Energy Convers. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"107504","DOI":"10.1016\/j.asoc.2021.107504","article-title":"Improved tunicate swarm algorithm: Solving the dynamic economic emission dispatch problems","volume":"108","author":"Li","year":"2021","journal-title":"Appl. Soft Comput."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"496","DOI":"10.1093\/ijlct\/ctaa014","article-title":"Capacity allocation of HESS in micro-grid based on ABC algorithm","volume":"15","author":"Zhang","year":"2020","journal-title":"Int. J. Low-Carbon Technol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"121823","DOI":"10.1016\/j.energy.2021.121823","article-title":"Multi-objective optimization model for fuel cell-based poly-generation energy systems","volume":"237","author":"Fragiacomo","year":"2021","journal-title":"Energy"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2125","DOI":"10.1063\/1.4904434","article-title":"Optimal configuration and analysis of combined cooling, heating, and power microgrid with thermal storage tank under uncertainty","volume":"7","author":"Gu","year":"2015","journal-title":"J. Renew. Sustain. Energy"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1016\/j.energy.2018.06.117","article-title":"Economic environmental unit commitment for integrated CCHP-thermal-heat only system with considerations for valve-point effect based on a heuristic optimization algorithm","volume":"159","author":"Olamaei","year":"2018","journal-title":"Energy"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"114356","DOI":"10.1016\/j.applthermaleng.2019.114356","article-title":"Stochastic dynamic solution for off-design operation optimization of combined cooling, heating, and power systems with energy storage","volume":"163","author":"Kuang","year":"2019","journal-title":"Appl. Therm. Eng."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.enconman.2017.03.058","article-title":"Modeling and optimal resources allocation of a novel tri-distributed generation system based on sustainable energy resources","volume":"143","author":"Soheyli","year":"2017","journal-title":"Energy Convers. Manag."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"115948","DOI":"10.1016\/j.energy.2019.115948","article-title":"A hybrid optimization-based scheduling strategy for combined cooling, heating, and power system with thermal energy storage","volume":"188","author":"Li","year":"2019","journal-title":"Energy"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1016\/j.energy.2018.12.079","article-title":"Optimal scheduling in a microgrid with a tidal generation","volume":"171","author":"Faridnia","year":"2019","journal-title":"Energy"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"124776","DOI":"10.1016\/j.jclepro.2020.124776","article-title":"Optimal performance of a combined heat-power system with a proton exchange membrane fuel cell using a developed marine predators algorithm","volume":"284","author":"Sun","year":"2021","journal-title":"J. Clean. Prod."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Mao, Y., Wu, J., and Zhang, W. (2020). An Effective Operation Strategy for CCHP System Integrated with Photovoltaic\/Thermal Panels and Thermal Energy Storage. Energies, 13.","DOI":"10.3390\/en13236418"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"121599","DOI":"10.1016\/j.energy.2021.121599","article-title":"Operation optimization of combined cooling, heating, and power superstructure system for satisfying demand fluctuation","volume":"237","author":"Chen","year":"2021","journal-title":"Energy"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"106592","DOI":"10.1016\/j.ijepes.2020.106592","article-title":"A dynamic decision-making method for energy transaction price of CCHP microgrids considering multiple uncertainties","volume":"127","author":"Zhao","year":"2021","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"107250","DOI":"10.1016\/j.cie.2021.107250","article-title":"Aquila Optimizer: A novel meta-heuristic optimization algorithm","volume":"157","author":"Abualigah","year":"2021","journal-title":"Comput. Ind. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Wang, S., Jia, H., Abualigah, L., Liu, Q., and Zheng, R. (2021). An Improved Hybrid Aquila Optimizer and Harris Hawks Algorithm for Solving Industrial Engineering Optimization Problems. Processes, 9.","DOI":"10.3390\/pr9091551"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"115579","DOI":"10.1016\/j.eswa.2021.115579","article-title":"Using enhanced crow search algorithm optimization-extreme learning machine model to forecast short-term wind power","volume":"184","author":"Li","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"125217","DOI":"10.1063\/5.0073335","article-title":"Shared seagull optimization algorithm with mutation operators for global optimization","volume":"11","author":"Ma","year":"2021","journal-title":"AIP Adv."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.apenergy.2014.08.107","article-title":"Combined cooling, heating and power: A review of performance improvement and optimization","volume":"136","author":"Cho","year":"2014","journal-title":"Appl. Energy"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"121407","DOI":"10.1016\/j.energy.2021.121407","article-title":"Dynamic economic emission dispatch considering renewable energy generation: A novel multi-objective optimization approach","volume":"235","author":"Liu","year":"2021","journal-title":"Energy"},{"key":"ref_29","first-page":"101326","article-title":"Modeling and analysis of a solar boosted biomass-driven combined cooling, heating and power plant for domestic applications","volume":"47","author":"Nami","year":"2021","journal-title":"Sustain. Energy Technol. Assess."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"7663","DOI":"10.1016\/j.egyr.2021.10.118","article-title":"Evaluation and optimization of PEM Fuel Cell-based CCHP system based on Modified Mayfly Optimization Algorithm","volume":"7","author":"Wei","year":"2021","journal-title":"Energy Rep."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"9984840","DOI":"10.1155\/2021\/9984840","article-title":"Optimization of Solar CCHP Systems with Collector Enhanced by Porous Media and Nanofluid","volume":"2021","author":"Tonekaboni","year":"2021","journal-title":"Math. Probl. Eng."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.enconman.2017.05.034","article-title":"Optimal design and analysis of a new CHP-HP integrated system","volume":"146","author":"Li","year":"2017","journal-title":"Energy Convers. Manag."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"7342","DOI":"10.1002\/er.5449","article-title":"Effect of storage options on price-based scheduling for a hybrid trigeneration system","volume":"44","author":"Nazari","year":"2020","journal-title":"Int. J. Energy Res."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Li, G., Wang, R., Zhang, T., and Ming, M. (2018). Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g. Energies, 11.","DOI":"10.3390\/en11040743"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1179","DOI":"10.1016\/j.cjche.2017.11.006","article-title":"An innovative trigeneration system using biogas as renewable energy","volume":"26","author":"Leonzio","year":"2018","journal-title":"Chin. J. Chem. Eng."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Dong, X., Quan, C., and Jiang, T. (2018). Optimal Planning of Integrated Energy Systems Based on Coupled CCHP. Energies, 11.","DOI":"10.3390\/en11102621"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1221","DOI":"10.1007\/s11630-019-1133-5","article-title":"Multi-Objective Particle Swarm Optimization (MOPSO) for a Distributed Energy System Integrated with Energy Storage","volume":"28","author":"Zhang","year":"2019","journal-title":"J. Therm. Sci."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"119990","DOI":"10.1016\/j.jclepro.2020.119990","article-title":"Design and evaluation of a solar-based trigeneration system for a nearly zero energy greenhouse in arid region","volume":"254","author":"Mohsenipour","year":"2020","journal-title":"J. Clean. Prod."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"De Souza, R., Casisi, M., Micheli, D., and Reini, M. (2021). A Review of Small-Medium Combined Heat and Power (CHP) Technologies and Their Role within the 100% Renewable Energy Systems Scenario. Energies, 14.","DOI":"10.3390\/en14175338"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Zhao, H., Lu, H., Wang, X., Li, B., Wang, Y., Liu, P., and Ma, Z. (2020). Research on Comprehensive Value of Electrical Energy Storage in CCHP Microgrid with Renewable Energy Based on Robust Optimization. Energies, 13.","DOI":"10.3390\/en13246526"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"109344","DOI":"10.1016\/j.rser.2019.109344","article-title":"An overview of optimization technologies applied in combined cooling, heating and power systems","volume":"114","author":"Gao","year":"2019","journal-title":"Renew. Sustain. Energy Rev."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"113529","DOI":"10.1016\/j.enconman.2020.113529","article-title":"Genetic algorithm-based operation strategy optimization and multi-criteria evaluation of distributed energy system for commercial buildings","volume":"226","author":"Wen","year":"2020","journal-title":"Energy Convers. Manag."},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Yousif, M., Ai, Q., Gao, Y., Wattoo, W., Jiang, Z., and Hao, R. (2018). Application of Particle Swarm Optimization to a Scheduling Strategy for Microgrids Coupled with Natural Gas Networks. Energies, 11.","DOI":"10.3390\/en11123499"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Wang, F., Zhou, L., Wang, B., Wang, Z., Shafie-Khah, M., and Catalao, J. (2017). Modified Chaos Particle Swarm Optimization-Based Optimized Operation Model for Stand-Alone CCHP Microgrid. Appl. Sci., 7.","DOI":"10.3390\/app7080754"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"812467","DOI":"10.3389\/fenrg.2021.812467","article-title":"Optimal PID Tuning of PLL for PV Inverter Based on Aquila Optimizer","volume":"9","author":"Guo","year":"2022","journal-title":"Front. Energy Res."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Fatani, A., Dahou, A., Al-qaness, M., Lu, S., and Elaziz, M. (2022). Advanced Feature Extraction and Selection Approach Using Deep Learning and Aquila Optimizer for IoT Intrusion Detection System. Sensors, 22.","DOI":"10.3390\/s22010140"},{"key":"ref_47","unstructured":"Deru, M., Field, K., and Studer, D. (2020, September 09). U.S. Department of Energy Commercial Reference Building Models of the National Building Stock, Available online: https:\/\/www.energy.gov\/eere\/buildings\/commercial-reference-buildings."},{"key":"ref_48","unstructured":"Wilson, E. (2020, September 09). Commercial and Residential Hourly Load Profiles for all TMY3 Locations in the United States. Available online: https:\/\/openei.org\/doe-opendata\/dataset\/commercial-and-residential-hourly-load-profiles-for-all-tmy3-locations-in-the-united-states."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/14\/4\/791\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:51:40Z","timestamp":1760136700000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/14\/4\/791"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,11]]},"references-count":48,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2022,4]]}},"alternative-id":["sym14040791"],"URL":"https:\/\/doi.org\/10.3390\/sym14040791","relation":{},"ISSN":["2073-8994"],"issn-type":[{"type":"electronic","value":"2073-8994"}],"subject":[],"published":{"date-parts":[[2022,4,11]]}}}